title: “Estimated change associated with the introduction of vaccine in”

Results

if (!is.null(names(analysis$sparse_groups[analysis$sparse_groups])) && length(names(analysis$sparse_groups[analysis$sparse_groups])) != 0) {
  kable(data.frame("Sparse Groups" = names(analysis$sparse_groups[analysis$sparse_groups]), check.names = FALSE), align = "c")
}

##combine estimates

if (params$crossval) {
  kable(cbind.data.frame(crossval_results$rr_mean_stack_intervals, impact_results$full$rr_mean_intervals, impact_results$time$rr_mean_intervals, impact_results$time_no_offset$rr_mean_intervals, impact_results$its$rr_mean_intervals, impact_results$pca$rr_mean_intervals), align = "c")
} else {
  kable(cbind.data.frame(impact_results$best$rr_mean_intervals, impact_results$full$rr_mean_intervals, impact_results$time$rr_mean_intervals, impact_results$time_no_offset$rr_mean_intervals, impact_results$its$rr_mean_intervals, impact_results$pca$rr_mean_intervals), align = "c")
}
Stacking Estimate (95% CI) Synthetic controls Estimate (95% CI) Time trend Estimate (95% CI) Time trend (no offset) Estimate (95% CI) Classic ITS (95% CI) STL+PCA Estimate (95% CI)
0 0.82 (0.75, 1.03) 0.81 (0.75, 0.95) 0.85 (0.73, 0.97) 0.96 (0.84, 1.1) 0.98 (0.83, 1.15) 0.94 (0.8, 1.09)
1 0.77 (0.72, 0.81) 0.77 (0.73, 0.81) 0.72 (0.62, 0.85) 0.84 (0.75, 0.95) 0.83 (0.75, 0.92) 0.84 (0.77, 0.92)

##Plot of Rate ratios, with size proportional to cross validation weights

##Weights for each of the models from cross validation

if (params$crossval) {
  kable(crossval_results$stacking_weights.all, align = "c")
} else {
  print("Cross-validation not performed")
}
groups Synthetic controls Time trend Time trend (no offset) STL+PCA
0 0.868 0.00 0.132 0
1 0.970 0.03 0.000 0

##Number of variables selected in SC analysis

kable(analysis$model_size, col.names = c("Model Size"))
Model Size
0 3.62
1 2.26

##Inclusion Probabilities

kable(incl_probs, align = "c")
Group Greatest Inclusion Variable Greatest Inclusion Probability Second Greatest Inclusion Variable Second Greatest Inclusion Probability Third Greatest Inclusion Variable Third Greatest Inclusion Probability
0 E00_99 1 cJ20_J22 1 S00_T99 0.4038685
1 E40_46 1 cJ20_J22 1 K00_99 0.0824349

##Weight Sensitivity Analysis

if (exists("sensitivity_results")) {
  kable(sensitivity_results$sensitivity_table_intervals, align = "c")
}
Estimate (95% CI) Top Control 1 Inclusion Probability of Control 1 Control 1 Estimate (95% CI) Top Control 2 Inclusion Probability of Control 2 Control 2 Estimate (95% CI) Top Control 3 Inclusion Probability of Control 3 Control 3 Estimate (95% CI)
0 0.81 (0.75, 0.95) cJ20_J22 1 0.85 (0.74, 1.04) E00_99 1 0.92 (0.77, 1.15) S00_T99 0.4 0.91 (0.74, 1.12)
1 0.77 (0.73, 0.81) cJ20_J22 1 0.75 (0.71, 0.8) E40_46 1 0.77 (0.72, 0.86) K00_99 0.08 0.76 (0.71, 0.82)

##Plots

for (group in names(plots$groups)) {
  for (group_plot in plots$groups[[group]]) {
    print(group_plot)
  }
}

##Print results